Local Promoter Methylation Disorder (LPMD) Algorithm Results for DNMT3A-mutant AML

A 2026 study by Xin Liu presents a Local Promoter Methylation Disorder (LPMD) algorithm for analyzing epigenetic instability in acute myeloid leukemia. The dataset includes results from multiple cohorts, including GSE62298 (68 patients), TCGA-LAML (194 patients), and a validation cohort for azacitidine response (63 patients). It contains algorithm outputs, differentially methylated disorder regions, and a 5-feature panel for predicting treatment response.

Use Cases

• Predicting azacitidine treatment response based on the 5-DMDR panel derived from multi-algorithm consensus.
• Analyzing methylation disorder patterns, such as bidirectional epigenetic disruption, associated with DNMT3A mutations.
• Monitoring treatment dynamics by tracking changes in LPMD scores over time, as shown in longitudinal sample analysis.
• Validating epigenetic instability metrics like Cohen's d effect sizes across different genomic regions (e.g., 5'UTR-Exon1, CpG islands).

Strengths

• Algorithm validated across multiple independent cohorts, including GSE62298 (n=68), TCGA-LAML (n=194), and a WGBS cohort (n=20).
• Predictive panel for azacitidine response achieved an AUC of 0.777 with 81% sensitivity and 73% specificity.
• Longitudinal analysis includes 153 samples for tracking treatment dynamics over a 3-5 month critical window.
• Identified 7,097 differentially methylated disorder regions (DMDRs) with a clear bidirectional pattern (85.3% decreased, 14.7% increased disorder).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific analytical tasks.
• Data is specific to acute myeloid leukemia and related myeloid malignancies, limiting generalizability to other cancers.

Provenance

Source

Xin Liu via figshare.

Collection Method

Algorithm development and analysis using public datasets (GSE62298, TCGA-LAML, GSE152710) and validation cohorts.

Freshness

Last updated 2026-03-18 05:21:23.